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Modelling Municipal Solid Waste Generation Using Geographically Weighted Regression: A Case Study of Nigeria

Author Affiliations

  • 11 Department of Urban and Regional Planning, Modibbo Adama University of Technology, Yola, NIGERIA
  • 2 Department of Surveying and Geoinformatics, Modibbo Adama University of Technology, Yola, NIGERIA
  • 3 Department of Geography, Adamawa State University, Mubi, NIGERIA

Int. Res. J. Environment Sci., Volume 4, Issue (8), Pages 98-108, August,22 (2015)


This study is aimed at developing a spatial model for municipal solid waste (MSW) generation rate based on socio-economic, demographic and climatic variables for Nigeria. The outcome is targeted at effective forecasting and management of MSW in the country. Secondary data sources were used to obtain the variables, then screened and linked to the administrative boundaries of the 36 States and the Federal Capital Territory (Abuja). Geographically Weighted Regression (GWR) tool in ArcGIS 10.0® was used to analyse the data. The analysis gives an acceptable condition number of 16.63, while local R ranges from 0.54 to 0.90. The model also explains 65 per cent of the total variation in the dependent variables. The findings of this study revealed that nearer States tend to have similar coefficients than the distant ones and that dependent variables vary among States. In addition, the coefficient estimates of unemployment rate, employment in crop farming, literate adults above 15 years, per-capita average household expenditure on food and non-food items, and excess proceeds of crude oil to local government areas exhibit positive relationship with MSW throughout the country. Whereas, only rainfall variable exhibited positive and negative relationship in northern and southern part of the country, respectively. The paper contributed towards improving the understanding of factors affecting MSW generation rate in Nigeria.


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